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EXTENDED ABSTRACT INTRODUCTION Investigating the link between monetary policy and stock returns has been very important for monetary policymakers and financial market investors to employ appropriate monetary policy and make the right investment decisions. Moreover, it has been of great interest to economists whether monetary policy has the same sort of effects in bull and bear stock market cycles. If a monetary policy has asymmetric impacts, policy makers should consider stock market cycles while implementing it. The objective of the present study is to investigate the reaction of stock returns to monetary policy and asymmetries over bull and bear cycles in Iran. Moreover, the impact of monetary policy on the switching probabilities between bull and bear regimes is also examined. The theoretical framework for explaining the asymmetries over stock market cycles can be described by the models with financial restrictions. According to these models, financial restrictions are more in bear cycles because of lower net worth in these periods. The lower the net worth, the greater the external finance premium should be. Higher external finance premium create a financial propagation mechanism which amplifies the interest rate effects of monetary policy (Garcia and Schaller, 2002; Chen, 2007). METHODOLOGY To examine asymmetries we employ Markov-switching (MS) models developed by Hamilton (1989). Unlike linear models this approach is nonlinear and can handle asymmetries. Besides, Hamilton algorithm endogenously determines bull and bear stock market cycles based on the data. In this study Hamilton (1989) MS model is modified to allow monetary policy to affect stock returns. Moreover, basic MS model is extended to a time-varying transition probability MS model (TVTP-MS) to allow the probability of switching between regimes depending on monetary policy. FINDINGS According to the findings MS models identify two regimes with different means and variances conventionally labelled as bull and bear. Average expected durations of bull and bear regimes show that both regimes are highly persistent. They persists on average around 10 to 12 quarters. The results of MS models show that monetary policy significantly affect stock returns only in bear cycles. When a monetary policy is measured by real M2, it has a positive impact on stock returns. However, when it is measured by real interest rate it negatively affects stock returns. In other words, an increase in real M2 raises stock returns while increasing real interest rate reduces returns.To measure the impact of monetary policy on the dynamics of switching between regimes we estimate a TVTP-MS model. The results indicate that an expansionary monetary policy raises the probability of remaining in a bull regime. Furthermore, an expansionary monetary policy reduces the probability of switching from a bull regime to a bear one. In addition, an expansionary monetary policy decreases the probability of being trapped in a bear market while it can increase the probability of switching from a bear market to a bull one. CONCLUSION The results of a modified MS model indicate that monetary policy significantly affect stock returns only in bear cycles. More specifically, increase in real M2 raises stock returns while increasing real interest rate reduce returns for both nominal and real returns in bear regimes. These findings are in line with the prediction of the models with financial restrictions. Finally, Empirical results from estimating TVTP-MS models suggest that an expansionary monetary policy raises the probability of remaining in a bull regime while reduces the probability of being trapped in a bear regime.As a policy implication, monetary policy makers should consider stock market cycles in implementing monetary policies. Especially in bear market periods implementing an expansionary monetary policy may lessen the probability of remaining in bear markets and will raise the probability of switching from a bear regime to a bull one. Moreover, stock market investors should consider that the impact of monetary policy on stock returns may depend on the phase of stock market.

The growing literature on teacher professional development emphasizes the positive contribution of teacher engagement to the professional development of teachers. However, scant attention was given to the relationship between this concept and teacher ecological agency as one of the potential factors influencing teacher engagement and in turn professional development. To fill this research gap, a sample of 369 EFL teachers from different institutes in Iran selected through convenience sampling participated in this study. The required data was collected by administering two questionnaires: The teacher ecological agency questionnaire and the teacher engagement questionnaire. The relationship between teachers’ ecological agency and teachers’ engagement and their underlying components were investigated through structural equation modeling (SEM) and Pearson correlation. The outcomes of SEM revealed a significant association between teachers’ ecological agency and engagement. The Pearson correlation results indicated that all three components of teacher ecological agency are correlated significantly with all five components of teacher engagement. The highest degree of correlation was found between emotional engagement and practical-evaluative agency (.711), agentic engagement, and practical-evaluative agency (.705) and cognitive engagement and practical-evaluative agency (.692). The pedagogical implications of this study enhance the efficiency of the educational system and teachers’ professional development.